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Top 43 explainable-ai open source projects

GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations
(Explainable AI) - Learning Non-Monotonic Logic Programs From Statistical Models Using High-Utility Itemset Mining
Explaining the output of machine learning models with more accurately estimated Shapley values
path explain
A repository for explaining feature attributions and feature interactions in deep neural networks.
Using deep learning to discover interpretable representations for mammogram classification and explanation
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
Explains machine learning models fast using the Anchor algorithm originally proposed by marcotcr in 2018
This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.
dlime experiments
In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
bert attn viz
Visualize BERT's self-attention layers on text classification tasks
ExpMRC: Explainability Evaluation for Machine Reading Comprehension
This Repo containes the implemnetation of generating Guided-GradCAM for 3D medical Imaging using Nifti file in tensorflow 2.0. Different input files can be used in that case need to edit the input to the Guided-gradCAM model.
Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020
Python library for Ceteris Paribus Plots (What-if plots)
self critical vqa
Code for NeurIPS 2019 paper ``Self-Critical Reasoning for Robust Visual Question Answering''
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